scholarly journals An Improved Bidirectional Shift-Based Reversible Data Hiding Scheme Using Double-Way Prediction Strategy

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Lin Li ◽  
Chin-Chen Chang ◽  
Hefeng Chen
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Prediction Errors ◽  
Threshold Values ◽  
Embedding Capacity ◽  
Stego Image ◽  
Original Algorithm ◽  
Prediction Error Expansion ◽  
Prediction Strategy

Reversible data hiding (RDH) is a method that allows a cover image to be completely recovered from its corresponding stego image without distortion after the embedded secret messages have been extracted. Prediction-error expansion (PEE), as a classic RDH scheme, has been studied extensively due to its high quality of stego images. Based on prediction errors, threshold values, and the relative distances between each bin and zero bin, we present a bidirectional shift and double-way prediction strategy to solve the multiple embedding problem. Compared with the original algorithm, this scheme only takes a little more time and reduces the PSNR slightly, but it improves the embedding capacity significantly and allows for reversible data hiding. When both threshold values of TH and TH∗ are equal to 2, the average ER value of 108 test images is 1.2 bpp which is ideal for medium data payload. At the same time, the PSNR is above 30 dB, making embedded information visually imperceptible. These data, together with other experimental results, show that the method proposed in this paper has obvious advantages in image quality and embedding capacity.

scholarly journals Taylor expansion based stereo image reversible data hiding

2020 ◽  
Author(s):  
Xinyang Ying ◽  
Guobing Zhou
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Taylor Expansion ◽  
Stereo Image ◽  
Embedding Capacity ◽  
Stereo Images ◽  
Secret Data ◽  
Stego Image ◽  
Multi Level

Abstract The reversible data hiding allows original image to be completely recovered from the stego image when the secret data has been extracted, it is has drawn a lot of attentions from researchers. In this paper, a novel Taylor Expansion (TE) based stereo image reversible data hiding method is presented. Since the prediction accuracy is essential to the data hiding performance, a novel TE based predictor using correlations of two views of the stereo image is proposed. TE can fully exploit strong relationships between matched pixels in the stereo image so that the accuracy of the prediction can be improved. Then, histogram shifting is utilized to embed data to decrease distortion of stereo images, and multi-level hiding can increase embedding capacity. Experimental results show that the proposed method is superior to some existing data hiding methods considering embedding capacity and the quality of the stego stereo images.

scholarly journals Hybrid Predictor and Field-Biased Context Pixel Selection Based on PPVO

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Hongyin Xiang ◽  
Jinsha Yuan ◽  
Sizu Hou
Keyword(s):  
Prediction Error ◽  
Reversible Data Hiding ◽  
State Of The Art ◽  
Prediction Errors ◽  
Embedding Capacity ◽  
Selection Technique ◽  
Expansion Strategy ◽  
Prediction Error Expansion ◽  
Pixel Value ◽  
Error Expansion

Most pixel-value-ordering (PVO) predictors generated prediction-errors including −1 and 1 in a block-by-block manner. Pixel-based PVO (PPVO) method provided a novel pixel scan strategy in a pixel-by-pixel way. Prediction-error bin 0 is expanded for embedding with the help of equalizing context pixels for prediction. In this paper, a PPVO-based hybrid predictor (HPPVO) is proposed as an extension. HPPVO predicts pixel in both positive and negative orientations. Assisted by expansion bins selection technique, this hybrid predictor presents an optimized prediction-error expansion strategy including bin 0. Furthermore, a novel field-biased context pixel selection is already developed, with which detailed correlations of around pixels are better exploited more than equalizing scheme merely. Experiment results show that the proposed HPPVO improves embedding capacity and enhances marked image fidelity. It also outperforms some other state-of-the-art methods of reversible data hiding, especially for moderate and large payloads.

A New Steganography Method Using Integer Wavelet Transform and Least Significant Bit Substitution

2019 ◽  
Vol 62 (11) ◽  
pp. 1639-1655
Author(s):  
Manashee Kalita ◽  
Themrichon Tuithung ◽  
Swanirbhar Majumder
Keyword(s):  
Wavelet Transform ◽  
Data Hiding ◽  
Integer Wavelet Transform ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Stego Image ◽  
Significant Similarity ◽  
Chi Squared ◽  
Integer Wavelet

Abstract Steganography is a data hiding technique, which is used for securing data. Both spatial and transform domains are used to implement a steganography method. In this paper, a novel transform domain method is proposed to provide a better data hiding method. The method uses a multi-resolution transform function, integer wavelet transform (IWT) that decomposes an image into four subbands: low-low, low-high, high-low and high-high subband. The proposed method utilizes only the three subbands keeping the low-low subband untouched which helps to improve the quality of the stego image. The method applies a coefficient value differencing approach to determine the number of secret bits to be embedded in the coefficients. The method shows a good performance in terms of embedding capacity, imperceptibility and robustness. A number of metrics are computed to show the quality of the stego image. It can also withstand RS steganalysis, Chi-squared test and Subtractive Pixel Adjacency Matrix steganalysis successfully. The deformation of the histogram and Pixel Difference Histogram for different embedding percentages are also demonstrated, which show a significant similarity with the original cover image. The proposed method shows an achievement of 2.3bpp embedding capacity with a good quality of stego image.

Enhanced stego-image quality and embedding capacity for the partial reversible data hiding scheme

2019 ◽  
Vol 78 (13) ◽  
pp. 18595-18616
Author(s):  
Ching-Nung Yang ◽  
Song-Yu Wu ◽  
Yung-Shun Chou ◽  
Cheonshik Kim
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Embedding Capacity ◽  
Stego Image

scholarly journals Efficient Lossless Compression Based Reversible Data Hiding Using Multilayered n-Bit Localization

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Rashid Abbasi ◽  
Lixiang Xu ◽  
Farhan Amin ◽  
Bin Luo
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Lossless Compression ◽  
Cover Image ◽  
Optimum Level ◽  
Embedding Capacity ◽  
Peak Point ◽  
Lower Block ◽  
Block Level

We proposed an innovative reversible data hiding technique that is formulated on histogram shifting by using multilayer localized n-bit truncation image (LBPTI), namely, generated form 8-bit plane by means of efficient lossless compression. After selecting the reference point from the block, the neighbor topmost points are used to attain the data embedding without modifying the peak point; in addition, the key information regarding peak point is not mandatory in extraction end to extract the secret information. In order to make the embedded cover-image similar to the histogram of original cover-image, we exploited the localization with efficient lossless compression on lower block level to increase the embedding capacity while controlling extra bit to expand additional embedding capacity on optimum level besides sustaining the quality of cover-image.

scholarly journals Histogram-based multilayer reversible data hiding method for securing secret data

2019 ◽  
Vol 8 (3) ◽  
pp. 1128-1134
Author(s):  
Chaidir Chalaf Islamy ◽  
Tohari Ahmad
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Experimental Results ◽  
Histogram Shifting ◽  
Secret Data ◽  
Stego Image ◽  
Sensitive Data ◽  
Modern Age ◽  
Potential Methods

In this modern age, data can be easily transferred within networks. This condition has brought the data vulnerable; so they need protection at all times. To minimize this threat, data hiding appears as one of the potential methods to secure data. This protection is done by embedding the secret into various types of data, such as an image. In this case, histogram shifting has been proposed; however, the amount of secret and the respective stego image are still challenging. In this research, we offer a method to improve its performance by performing some steps, for example removing the shifting process and employing multilayer embedding. Here, the embedding is done directly to the peak of the histogram which has been generated by the cover. The experimental results show that this proposed method has a better quality of stego image than existing ones. So, it can be one of possible solutions to protect sensitive data.

scholarly journals AN EFFECTIVE REVERSIBLE DATA HIDING METHOD BASED ON PIXEL-VALUE-ORDERING

2020 ◽  
Vol 36 (2) ◽  
pp. 139-158
Author(s):  
Nguyen Kim Sao ◽  
Nguyen Ngoc Hoa ◽  
Pham Van At
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
New Method ◽  
Embedding Capacity ◽  
Stego Image ◽  
Pixel Value ◽  
Using Data ◽  
Location Map ◽  
Better Than

This paper presents a new effective reversible data hiding method based on pixel-value-ordering (iGePVO-K) which is improvement of a recent GePVO-K method that recently is considered as a PVO-used method having highest embedding capacity. In comparison with GePVO-K method, iGePVO-K has the following advantages. First, the embedding capacity of the new method is higher than that of GePVO-K method by using data embedding formulas reasonably and reducing the location map size. Second, for embedding data, in the new method, each pixel value is modified at most by one, while in GePVO-K method, each pixel value may be modified by two. In fact, in the GePVO-K method, the largest pixels are modified by two for embedding bits 1 and by one for bits 0. This is also true for the smallest pixels. Meanwhile, in the proposed method, the largest pixels are modified by one for embedding bits 1 and are unchanged if embedding bits 0. Therefore, the stego-image quality in proposed method is better than that in GePVO-K method. Theoretical analysis and experiment results show that the proposed method has higher embedding capacity and better stego image quality than GePVO-K method.

High-Capacity Reversible Data Hiding Using Modified Pixel Value Ordering Approach

2018 ◽  
Vol 27 (11) ◽  
pp. 1850175 ◽  
Author(s):  
Neeraj Kumar Jain ◽  
Singara Singh Kasana
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Visual Quality ◽  
Experimental Results ◽  
Cover Image ◽  
Embedding Capacity ◽  
Signal Process ◽  
Pixel Value

The proposed reversible data hiding technique is the extension of Peng et al.’s technique [F. Peng, X. Li and B. Yang, Improved PVO-based reversible data hiding, Digit. Signal Process. 25 (2014) 255–265]. In this technique, a cover image is segmented into nonoverlapping blocks of equal size. Each block is sorted in ascending order and then differences are calculated on the basis of locations of its largest and second largest pixel values. Negative predicted differences are utilized to create empty spaces which further enhance the embedding capacity of the proposed technique. Also, the already sorted blocks are used to enhance the visual quality of marked images as pixels of these blocks are more correlated than the unsorted pixels of the block. Experimental results show the effectiveness of the proposed technique.

scholarly journals A Novel Reversible Data Hiding Method for 3D Model in Homomorphic Encryption Domain

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1090
Author(s):  
Ting Luo ◽  
Li Li ◽  
Shanqin Zhang ◽  
Shenxian Wang ◽  
Wei Gu
Keyword(s):  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
3D Model ◽  
Homomorphic Encryption ◽  
Cloud Service ◽  
3D Models ◽  
Embedding Capacity ◽  
Secret Data ◽  
Prediction Error Expansion

Reversible data hiding in the encrypted domain (RDH-ED) is a technique that protects the privacy of multimedia in the cloud service. In order to manage three-dimensional (3D) models, a novel RDH-ED based on prediction error expansion (PEE) is proposed. First, the homomorphic Paillier cryptosystem is utilized to encrypt the 3D model for transmission to the cloud. In the data hiding, a greedy algorithm is employed to classify vertices of 3D models into reference and embedded sets in order to increase the embedding capacity. The prediction value of the embedded vertex is computed by using the reference vertex, and then the module length of the prediction error is expanded to embed data. In the receiving side, the data extraction is symmetric to the data embedding, and the range of the module length is compared to extract the secret data. Meanwhile, the original 3D model can be recovered with the help of the reference vertex. The experimental results show that the proposed method can achieve greater embedding capacity compared with the existing RDH-ED methods.

Reversible Data Hiding Based on Statistical Correlation of Blocked Sub-Sampled Image

2012 ◽  
Vol 2 (1) ◽  
pp. 42-59
Author(s):  
Mona Nafari ◽  
Mansour Nejati Jahromi ◽  
Gholam Hosein Sheisi
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Statistical Correlation ◽  
Experimental Results ◽  
Data Embedding ◽  
Embedding Capacity ◽  
Stego Image

In this paper, a reversible data hiding scheme has been proposed which is based on correlation of subsample images. The proposed method modifies the blocks of sub-sampled image to prepare vacant positions for data embedding. The PSNR of the stego image produced by the proposed method is guaranteed to be above 47.5 dB, while the embedding capacity is at least, almost 6.5 times higher than that of the Kim et al. techniques with the same PSNR. This technique has the capability to control the capacity-PSNR. Experimental results support that the proposed method exploits the correlation of blocked sub-sampled image outperforms the prior works in terms of larger capacity and stego image quality. On various test images, the authors demonstrate the validity of the proposed method by comparing it with other existing reversible data hiding algorithms.

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